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GPM, DPR, GMI Level 3 Combined Precipitation V03
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:03:54.000ZThere are uncertainties in the interpretation of data from any one of the instruments (KuPR, KaPR, and GMI). By using data from multiple instruments, further constraints on the solution of precipitation structure improve the final product.The purpose of 3CMB is to give a daily and monthly accumulation of the 2BCMB precipitation product. The 3CMB product is a daily and monthly accumulation of the 2BCMB orbital combined product at two grid sizes, 5 x 5 degrees (G1) and 0.25 x 0.25 degrees (G2). Grid G1 contains the following physical measurements of general interest, among others. Grid G2 contains the same groups, but it is on the ltH x lnH grid and does not have the surface type (st) dimension or the histograms (see dimension definitions below). Below, conditional products represent means based upon precipitating areas only; unconditional products represent means for raining and non-raining areas combined. Probabilities represent the number of raining observations divided by the total number of raining and non-raining observations. precipTotRate (Group in G1)- Conditional mean rate for all precipitation phases (ice, liquid, mixed-phase). * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqRate (Group in G1) - Conditional mean rate for liquid precipitation. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotWaterContent (Group in G1) - Conditional mean water content for all precipitation phases. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqWaterContent (Group in G1) - Conditional mean liquid water content. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotDm (Group in G1) - Conditional mass-weighted mean particle diameter. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotRateDiurnal (Group in G1) - Conditional mean total surface precipitation rate indexed by local time. * count (4-byte integer, array size: ltL x lnL x ns x st x tim): Count. * mean (4-byte float, array size: ltL x lnL x ns x st x tim): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x st x tim): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. surfPrecipTotRateDiurnalAllObs (4-byte integer, array size: ltL x lnL x ns x st x tim): Number of total observa...
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Combining Discrete Element Modeling, Finite Element Analysis, and Experimental Calibrations for Modeling of Granular Material Systems Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:43:27.000ZThe current state-of-the-art in DEM modeling has two major limitations which must be overcome to ensure that the technique can be useful to NASA engineers and the commercial sector: the computational intensive nature of the software, and the lack of an established methodology to determine the particle properties to best accurately model a given physical system. The proposed work will address both of these limitations. We will look at two approaches to overcome the particle count limitations of DEM: investigate the scaling up of particle size; and combine FEA and DEM to look at problems of densely packed solids. We will explore regimes where DEM and FEA are applicable and establish a coupling methodology that can be further developed during phase II. To address the lack of an established methodology to determine the particle properties to best accurately model a given physical system, we will investigate several small scale experiments that can be used to characterize DEM models. The proposed work will advance the state-of-the-art in DEM. At the end of phase I we will show the feasibility of developing modeling approaches to overcome the main limitations of DEM.
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TRMM Microwave Imager (TMI) Gridded Oceanic Rainfall Product (TRMM Product 3A11) V7
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:52:56.000ZThe Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating. TRMM was successfully launched on November 27, at 4:27 PM (EST) from the Tanegashima Space Center in Japan. The TRMM Microwave Imager (TMI) is a nine-channel passive microwave radiometer, which builds on the heritage of the Special Sensor Microwave/Imager (SSM/I) instrument flown aboard the Defense Meteorological Satellite Program (DMSP) platforms. Microwave radiation is emitted by the Earth's surface and by water droplets within clouds. However, when layers of large ice particles are present in upper cloud regions - a condition highly correlated with heavy rainfall - microwave radiation tends to scatter at frequencies above 19 GHz. The TMI detects radiation at five frequencies chosen to discriminate among these processes, thus revealing the likelihood of rainfall. The key to accurate retrieval of rainfall rates by this method is the deduction of cloud precipitation consistent with the radiation measurement at each frequency. The TMI frequencies are 10.65, 19.35, 37 and 85.5 GHz (dual polarization), and 21 GHz (vertical polarization only). The TMI Gridded Oceanic Rainfall Product, also known as TMI Emission, consists of 5 degree by 5 degree monthly oceanic rainfall maps using TMI Level 1 data as input. Statistics of the monthly rainfall, including number of samples, standard deviation, goodness-of-fit (of the brightness temperature histogram to the lognormal rainfall distribution function) and rainfall probability are also included in the output for each grid box. Spatial coverage is between 40 degrees North and 40 degrees South owing to the 35 degree inclination of the TRMM satellite. TMI brightness temperature histograms at 1 degree intervals are generated based on the 19, 21 and 19-21 GHz combination channels obtained from the Level 1B (calibrated brightness temperature) TMI product. Monthly rainfall indices over the ocean are derived by statistically matching monthly histograms of brightness temperatures with model calculated rainfall Probability Distribution Functions (PDF) using the 19-21 GHz combination data. Retrieved monthly rainfall data must pass a quality test based on the quality of the PDF fit. The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata applicable to the TMI measurements. A file contains 12 arrays of rainfall data and supporting information each of dimension 72 x 16, with a file size of about 40 KB (uncompressed). The HDF-EOS "grid" structure is used to accommodate the actual geophysical data arrays. There is 1 file of TMI 3A11 data produced per month.
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Robust Optimal Fragmentation and Dispersion of Near-Earth Objects Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:31:30.000Z<p> During the past 2 decades, various concepts for mitigating the impact threats from NEOs have been proposed, but many of these concepts were impractical and not technically credible. In particular, all non-nuclear techniques require mission lead times larger than 10 years. However, for the most probable impact threat with a warning time less than 10 years, the use of high-energy nuclear explosives in space becomes inevitable for proper fragmentation and dispersion of an NEO in a collision course with Earth. However, the existing nuclear subsurface penetrator technology limits the impact velocity to less than 300m/s because higher impact velocities destroy prematurely the detonation electronic equipment. Thus, an innovative space system architecture utilizing high-energy nuclear explosives must be developed for a worst-case intercept mission resulting in relative closing velocities as high as 5-30km/s. An advanced system concept is proposed for nuclear subsurface explosion missions. The concept blends a hypervelocity kinetic-energy impactor with nuclear subsurface explosion, and exploits a 2-body space vehicle consisting of a fore body and an aft body. These 2 spacecraft bodies may be connected by a deployable boom. The fore body provides proper kinetic impact crater conditions for an aft body carrying nuclear explosives to make a deeper penetration into an asteroid body. For such a complex mission architecture design study, non-traditional, multidisciplinary research efforts in the areas of hypervelocity impact dynamics, nuclear explosion modeling, high-temperature thermal shielding, shock-resistant electronic systems, and advanced space system technologies are required. Expanding upon the current research activities, the Iowa State Asteroid Deflection Research Center will develop an innovative, advanced space system architecture that provides the planetary defense capabilities needed to enable a future real space mission more efficient, affordable, and reliable.</p>
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TRMM Microwave Imager (TMI) Gridded Oceanic Rainfall Product (TRMM Product 3A11) V7
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:52:56.000ZThe Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating. TRMM was successfully launched on November 27, at 4:27 PM (EST) from the Tanegashima Space Center in Japan. The TRMM Microwave Imager (TMI) is a nine-channel passive microwave radiometer, which builds on the heritage of the Special Sensor Microwave/Imager (SSM/I) instrument flown aboard the Defense Meteorological Satellite Program (DMSP) platforms. Microwave radiation is emitted by the Earth's surface and by water droplets within clouds. However, when layers of large ice particles are present in upper cloud regions - a condition highly correlated with heavy rainfall - microwave radiation tends to scatter at frequencies above 19 GHz. The TMI detects radiation at five frequencies chosen to discriminate among these processes, thus revealing the likelihood of rainfall. The key to accurate retrieval of rainfall rates by this method is the deduction of cloud precipitation consistent with the radiation measurement at each frequency. The TMI frequencies are 10.65, 19.35, 37 and 85.5 GHz (dual polarization), and 21 GHz (vertical polarization only). The TMI Gridded Oceanic Rainfall Product, also known as TMI Emission, consists of 5 degree by 5 degree monthly oceanic rainfall maps using TMI Level 1 data as input. Statistics of the monthly rainfall, including number of samples, standard deviation, goodness-of-fit (of the brightness temperature histogram to the lognormal rainfall distribution function) and rainfall probability are also included in the output for each grid box. Spatial coverage is between 40 degrees North and 40 degrees South owing to the 35 degree inclination of the TRMM satellite. TMI brightness temperature histograms at 1 degree intervals are generated based on the 19, 21 and 19-21 GHz combination channels obtained from the Level 1B (calibrated brightness temperature) TMI product. Monthly rainfall indices over the ocean are derived by statistically matching monthly histograms of brightness temperatures with model calculated rainfall Probability Distribution Functions (PDF) using the 19-21 GHz combination data. Retrieved monthly rainfall data must pass a quality test based on the quality of the PDF fit. The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata applicable to the TMI measurements. A file contains 12 arrays of rainfall data and supporting information each of dimension 72 x 16, with a file size of about 40 KB (uncompressed). The HDF-EOS "grid" structure is used to accommodate the actual geophysical data arrays. There is 1 file of TMI 3A11 data produced per month.
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GPM GROUND VALIDATION NASA S-BAND DUAL POLARIMETRIC (NPOL) DOPPLER RADAR IFLOODS V2
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:47:13.000ZThe GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloods V2 data set was collected from April 30, 2013 to June 16, 2013 near Traer, Iowa as a part of the Global Precipitation Measurement Mission (GPM) Iowa Flood Studies (IFloodS) campaign. The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, Doppler research radar that collected and operated nearly continuously during the IFloodS field campaign. The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS V2 data is available in Universal [Radar] Format (UF).
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Wire Insulation Incorporating Self-Healing Polymers (WIISP) Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:44:05.000ZNextGen Aeronautics, Inc. and their partner, Virginia Tech, propose to develop a self-healing material for wire insulation using a class of poly(ethylene-co-methacrylic acid) (EMAA) and poly(tetramethylene oxide) ionomer polymers. The self-healing property of these materials is strongly correlated with the thermal processes that occur during and after damage initiation. Recent experimental results have demonstrated that penetration of the polymer by a projectile causes localized heating near the puncture. The heating then causes a localized melt elastic response which serves to close the puncture and 'heal' the polymer. Since self-healing has already been demonstrated using these materials, the major technical challenge of this STTR effort is to stimulate the localized melt elastic response that has been shown to initiate self-healing. Our concept is to incorporate a magnetically-response phase into the insulating polymer for the purpose of causing localized heating during high-frequency excitation of the polymer. This magnetic phase will be located close to the electrical conductor. Localized heating will cause flow into the crack and, upon cooling, the crack will close over the wire and eliminate the exposure of the bare wire.
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Mobile Passive Optical Imager for Remote Gas Detection Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:38:03.000ZTunable filters based on electro-optic effect have shown great potential in detecting gas concentration through obtaining its absorption spectrum. In filter-based technologies, the x-y 2D imaging is usually taken at once, while the wavelength dimension is performed by tunable filters that are mounted in front of a monochrome IR camera. Several types of tunable filters are currently available, including mechanically tuned Fabry-Perot etalon (FP filter), liquid-crystal Lyot-Ohman filters and acousto-optic filters. However, these EO tuning technologies have some shortages, such as slow tuning speed, bulky design, limited working band and small aperture. Boston Applied Technologies, Inc. (BATi) proposes a unique remote sensing system which is based on a tunable filter with under millisecond tuning time for high speed detection of gas concentration. The core part, tunable filter, of the proposed system is made of patented OptoCeramic&#174; material. The system features high speed, wide spectral range from visible to MWIR, low cost, light weight, big aperture, and robust.
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GPM GROUND VALIDATION NASA S-BAND DUAL POLARIMETRIC (NPOL) DOPPLER RADAR IFLOODS V2
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:47:14.000ZThe GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloods V2 data set was collected from April 30, 2013 to June 16, 2013 near Traer, Iowa as a part of the Global Precipitation Measurement Mission (GPM) Iowa Flood Studies (IFloodS) campaign. The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, Doppler research radar that collected and operated nearly continuously during the IFloodS field campaign. The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS V2 data is available in Universal [Radar] Format (UF).
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Superconducting Electric Boost Pump for Nuclear Thermal Propulsion Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:34:52.000ZA submersible, superconducting electric boost pump sized to meet the needs of future Nuclear Thermal Propulsion systems in the 25,000 lbf thrust range is proposed. The proposed solution combines active electronic speed control technology with state-of-the-art cavitation suppression techniques to meet the near-zero Net Positive Suction Head requirements with up to 50% vapor content and enables a higher level of safety, reliability and operability for the Nuclear Thermal Propulsion (NTP) system than turbine driven pumps. The proposed pump configuration enables placement in, or close-coupled to the tank where it can be shielded from the reactor to prevent neutron flux heating. Evaluation of NTP power cycles will enable feasibility determination for driving the boost pump, and possibly the main pump, electrically and provides a comparison of approaches for the derivation of requirements needed in the development of an ultra-long life, highly reliable integrated pump system for NTP. The requirements, system trades and benefits analysis, conceptual design, risk reduction and Phase II planning will be documented to enable further development and TRL transition from TRL 3 at the completion of Phase I to TRL 5 at the completion of Phase II.